CBMS Regional Research Conference on Topological Data Analysis

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The conference, "Topological Data Analysis: Theory and Applications," will take place at Macalaster College (St. Paul, MN) from June 12-16, 2017. Topological Data Analysis (TDA) is a relatively recent and quickly-developing area of research at the intersection of mathematics, statistics, and computer science. The goal of the conference is to encourage research in TDA by faculty and students, especially at primarily undergraduate institutions, who might not have prior experience with TDA. As such, this conference will attract faculty, graduate students, and advanced undergraduates from colleges and universities across the upper Midwestern states. The conference is designed to equip attendees with not only the theoretical framework of TDA, but also practical computational tools, providing points of entry so that faculty and students from diverse settings can begin research in topological data analysis and incorporate this work into their teaching. The conference will spur new research collaborations between institutions and across disciplines. The resulting monograph, prepared by principal lecturer Dr. Vin de Silva, Associate Professor of Mathematics at Pomona College, should be of interest to mathematicians, scientists and students. In recent years, Topological Data Analysis (TDA) has attracted widespread interest from mathematicians and scientists looking for new tools to analyze ever increasing amounts of complex data arising from neuroscience, digital imaging, genetics, biological aggregations, sensor networks, cancer research, and other areas. The intellectual appeal of TDA arises from its combination of advanced mathematics, cutting-edge algorithms, and practical applications. Yet, despite its mathematical sophistication, TDA methodology is surprisingly intuitive and lends itself well to research with students, even at the undergraduate level. The principal lecturer at this conference will be Dr. Vin de Silva who has been a key contributor to the development of TDA. Lecture topics will include winding numbers, simplicial homology and cohomology, the persistence algorithm, stability theorems, zigzag persistence, category theory and generalized persistence, and Reeb cosheaves. In addition to lectures, the conference will feature lab sessions that will offer participants hands-on experience analyzing real data using state-of-the-art TDA software, as well as a poster session highlighting TDA research involving students. This conference will focus on mathematics and computation rather than statistics, and it will emphasize research in the setting of primarily undergraduate institutions.Information about the conference is available at http://pages.stolaf.edu/tda-conference/